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The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

Purpose – The purpose of this paper to immobilization provides biosorbent particle with density and mechanichal strength, immobilization can save the cost of separating from biomass, can be regeneration and to increase adsorption capacity for metal ions.

Design/Methodology/Approach – The parameters affecting the adsorption, such as initial metal ion concentration, pH, contact time, and temperature, were studied. The analysis of biosorbent functional group was carried out by Fourier Transform Infrared Spectroscopy, SEM-EDX, for elemental analysis.

Findings – Optimum pH condition for biosorption Cd(II) was pH 5, contact time was 45 min, and initial concentration was 250 mg/L. Biosorbent analysis was characterized using SEM-EDX and FTIR analysis. Kinetics adsorption was studied and analyzed in terms of the pseudo-first-order, pseudo-second-order, and intraparticle diffusion kinetics models. The result showed that the biosorption for Cd(II) ion followed the pseudo-second-order kinetic model. Biosorption data of Cd(II) ion at 300°K, 308°K, and 318°K was analyzed with Temkin, Langmuir, and Freundlich isotherms. Biosorption of Cd(II) by durian seed immobilization in alginate according to the Langmuir isotherm equation provided a coefficient correlation of r² = 0.939 and maximum capacity biosorption of 25.05 mg/g.

Purpose – In this study, the possibility of the application of rice husks for adsorbing Mn(II) ion in the water phase has been studied.

Design/Methodology/Approach – Experimental studies have been initiated by preparing activated carbon from rice husks. The activation of rice husks was done using both physical and chemical treatment methods through heating at 110 °C and washing with citric acid activator at 0.2 M, 0.4 M, and 0.6 M. The adsorption tests were conducted as two part tests: preliminary and primary. The preliminary test was conducted to choose the best condition of four independent variables, i.e., contact time (0–120 minutes), activator concentrations (0.2, 0.4, and 0.6 M), initial Mn(II) concentrations (10, 20, 50, 100, 200, and 400 mg/L), and adsorption temperatures (30, 47, and 67 °C).

Findings – By identifying the substituted groups using Fourier Transform Infrared Spectroscopy after activation with citric acid, it was found that the highest transmittance percentage was present in activated carbon with 0.2 M of citric acid. The best adsorption capacity and efficiency was 13.87 mg/g and 79.60%, respectively, which were obtained at 200 mg/L initial concentration with a 0.2 M citric acid concentration for 120 min contact time at 47 °C. These results lead to a conclusion that rice husks after activation with citric acid can be applied as an adsorbent for Mn(II) adsorption in the water phase.

Research Limitations/Implications – The activated carbon produced was only applicable for the adsorption of Mn(II) ions from the water phase, but not applicable for the adsorption of other heavy metals ions.

Practical Implications – Rice husks were potentially prepared as an adsorbent for Mn(II) ion adsorption in the water phase that was low cost, environmental friendly, and easy to prepare.

Originality/Value – Activated carbon prepared from biomass was mostly carried out using acids at high concentrations while the study was conducted using weak acids (citric acid) at low concentrations.